Evidence map›Paper›PMID 41001117›Full record

ArticleResearch (Washington, D.C.)2025

Flexible Self-Powered Respiration Sensor Inspired by Fish Lateral Line Systems.

Guoliang Ma, Mengze Zhang, Guozhao Shi, Congtian Gu, Hu Shen, Kaixian Ba, Yijie Zhang, Dakai Wang, Xizhao Liu, Bin Yu and 2 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Research (Washington, D.C.), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Review
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

12 authors.

Guoliang MaState Key Laboratory of Crane Technology, Yanshan University, Qinhuangdao 066000, China.ORCID https://orcid.org/0009-0005-0371-3799
Mengze ZhangState Key Laboratory of Crane Technology, Yanshan University, Qinhuangdao 066000, China.
Guozhao ShiState Key Laboratory of Crane Technology, Yanshan University, Qinhuangdao 066000, China.
Congtian GuState Key Laboratory of Crane Technology, Yanshan University, Qinhuangdao 066000, China.
Hu ShenState Key Laboratory of Crane Technology, Yanshan University, Qinhuangdao 066000, China.
Kaixian BaState Key Laboratory of Crane Technology, Yanshan University, Qinhuangdao 066000, China.
Yijie ZhangResearch Institute of Yanshan University, Shenzhen 518063, China.
Dakai WangKey Laboratory of Bionic Engineering, Ministry of Education, Jilin University, Changchun 130022, China.
Xizhao LiuSchool of Public Administration, Yanshan University, Qinhuangdao 066004, China.
Bin YuState Key Laboratory of Crane Technology, Yanshan University, Qinhuangdao 066000, China.
Zhiwu HanKey Laboratory of Bionic Engineering, Ministry of Education, Jilin University, Changchun 130022, China.
Luquan RenKey Laboratory of Bionic Engineering, Ministry of Education, Jilin University, Changchun 130022, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Respiration is a critical physiological signal, and abnormal respiratory patterns are widely recognized as key indicators of various cardiopulmonary and neurological disorders, making continuous monitoring crucial. However, existing clinical systems are constrained by motion limitations, complexity, and cost, hindering daily use. In this work, we present a bio-inspired, low-cost, flexible, and self-powered respiration sensor (BLFS-RS) inspired by the fish lateral line system, operating via contact electrification and electrostatic induction. It features a semicylindrical structure made of silicone rubber, incorporating bionic air channels and a porous-villus composite microstructure. It detects respiratory forces by deforming with abdominal cavity fluctuations, enabling respiration monitoring. Experimental results show that the incorporation of the porous-villus structure increases the sensor's peak output voltage by 556% compared to a nonstructured counterpart. Additionally, the BLFS-RS exhibits high sensitivity (0.88 V/kPa), high durability (300,000 cycles), and fast response time (48 ms). A wearable real-time respiratory monitoring system based on BLFS-RS enables the acquisition of a comprehensive range of human respiratory parameters, including respiratory rate, apnea-hypopnea index, and peak expiratory flow. Furthermore, patients suffering from speech impairments can utilize the BLFS-RS for alternative communication by encoding information through distinct respiratory patterns. This work is expected to provide a viable and sustainable solution for personalized healthcare and remote respiratory monitoring.

Identifiers

PMID41001117
PMCPMC12457744

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.